Method to correct ion source inefficiencies makes sample-to-sample normalization possible

ABSTRACT

In mass spectrometry significant error is introduced during sample preparation (sample-to-sample error), during ion generation (ion suppression), and during ion transmission (ion transmission losses). We demonstrate the ability to correct for ion suppression and ion transmission losses, and that once corrected for ion losses, a sample-to-sample normalization of the analytical sample to the internal standard is possible. By normalizing to a standard sample the analytical sample becomes completely comparable to any similarly treated sample.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. application 62/688846 filed onJun. 22, 2018, whose disclosures are incorporated by reference.

BACKGROUND ART

Traditionally, mass spectrometry is not considered a good quantitativemethod because of the variability that is frequently introduced in ionsources due to either the inefficiencies of ion generation, or iontransmission. For this reason, in situations where accurate quantitationis desired internal standards and a clean “base-line” chromatographicseparation are required. This practice becomes expensive and awkward asthe number of compounds to be measured increases; therefore in mostcases the number of compounds to be quantified is kept small andinternal standards with well-defined chemical concentrations andcomposition are employed.

The actual act of quantitation is done on a compound-by-compound basisand quantitation is achieved by directly comparing the quantity ofinternal standard to the quantity of analyte; i.e., the ratio of theanalyte to internal standard is multiplied by the known quantity of theinternal standard. This achieves a better quantitative solution for eachcompound than the raw data that was originally acquired since it almostalways suffered from some ion losses.

The present invention takes a global approach that corrects the wholesample and reaps the additional benefits of normalization and directlyquantifying the percent of losses for each compound. There is no knownprior literature that has taken this approach.

The variances seen in the ion sources of most mass spectrometers arisefrom ionization losses during two distinct parts of the analyticalprocesses required; namely, the generation and transmission of the ionsthat are measured. Ion suppression is a general term that applies to ionlosses or inefficiencies that occur during the process of the generationof ions. Additional ion losses occur during the transmission of ionsthrough source and mass analyzer. These two processes cause ion lossesor variance, but they are very different in their nature.

Ion suppression losses vary compound by compound and are sensitive tothe environment in which an ion is created therefore they vary sample tosample, while the ion losses due to a source's geometries, andelectronics are subject to significant change, but are stable forextended periods of time; both create different kinds of problems forthe mass spectroscopist as they reduce the overall sample-to-samplecomparability, short-term and long-term.

Metabolomics analyses are currently divided into two main methods{Fiehn¹}, namely, targeted {Roberts²} and non-targeted {Vinayavekhin³}analyses. Although, by definition, almost all clinical measurements aretargeted, most of these measurements are not part of metabolomicinvestigations, so by far, the largest number of metabolomicinvestigations start with non-targeted, often called “unbiased”,analyses.

The beauty of the non-targeted analysis is that it makes no presumptionsas to the class of molecules that need be investigated and thus, isconsidered a good means of hypothesis generation and the first step in alarger series of “discovery” investigations. Unfortunately, thetechniques generally employed in non-targeted analyses have at theirheart a series of assumptions that are often forgotten ormis-understood.

The three most serious of these assumptions are that 1) ion suppression,often called matrix effect (ME), is likely consistent across all samplesfor a given sample type, and therefore may be ignored; 2) iontransmission losses will not change significantly during the run time ofa given experiment; and 3) that the samples are similar enough in sizeand form that normalization is either simple or un-necessary.

As discussed hereinafter, all three of these assumptions are related andall three can be corrected once they are related to one another.Although initially applied to metabolomics the present solution appliesto all situations where a large number of compounds need to bequantitated using a chemically complex internal standard, ornormalization is based on corrected data.

Ion suppression (suppression) is a well characterized {Annesley⁴,Trufelli⁵, Jessome⁶}, though poorly understood, phenomenon having to dowith the variance of the efficiency of ionization of any molecule. Firstdescribed in the early 1990's by Kebarle {Ikonomou⁷, Kebarle⁸, andTang⁹}, ion suppression is considered to be present to some extend inalmost all ionization sources, including MALDI {Knochenmuss¹⁰} andDESI/MALDI {Taylor¹¹}, but it is particularly an issue with the mostcommon sources used today, the ElectroSpray Ionization source (ESI) andAtmospheric Pressure Chemical Ionization (APCI) {Ismaiel¹²}.

In general, suppression is considered a complex function of molecularstructure that involves all of a compound's physical parameters; i.e.,acidity/basicity, polarity/aromaticity, hydrophobicity/lipophilicity,electronic and physical structures, the concentration of the compounditself {Annesley⁴}, the nature of the source, elution solvents, gastemperature, and the general chemical environment and complexity of theeffluent in which the compound elutes.

It has been shown that reduction of chemical complexity of the samples,e.g. during sample preparation by solid phase extraction (SPE), or bybase-line chromatographic separation, can reduce suppression for somecompounds but, neither of these methods completely removes suppression{Vats¹³}. Similarly, reduction of the total concentration of a compound,for instance by use of nanoSpray sources, will again reduce, but notremove suppression {Temesi¹⁴}.

Because suppression occurs in the ionization processes of the source,suppression is a phenomenon relevant to all post-source MS processes,including ms/ms {Freitas¹⁵}. Suppression is dependent upon the chemicalproperties of the analyte as it passes into the source and varies inintensity of suppression for each compound as a function ofconcentration; i.e., it is never stable, and even slight variations ofthe chromatographic process, ion source, solvent, or temperature canalter it.

The most common way to correct for the effects of ion suppression isthrough the use of internal standards {Baillie¹⁶} that became called“Stable isotope dilution-mass spectrometry” (SID-MS) {Leenheer¹⁷}. Whenthe number of compounds being measured is small, use of individualaliquots of purified isotopic standard, SID-MS, represents the optimalsolution. However, as the number of compounds that needs to be measuredincreases, the economics become untenable.

Therefore, techniques such as MIRACLE {Mashego¹⁸, Wu¹⁹} based onisotopically enriched biological mixtures were developed; however, thedifficulty of identifying the isotopic peaks amongst the others madethis technique difficult to use in practice. Other attempts at usingisotopic internal standards have tried using a single representativecompound as a standard for other compounds of that class. However, aswas noted above the immediate source environment is a critical componentof suppression, and the likelihood that the standard compound issuffering the same level of suppression as the analyte is difficult toassure if they are in different environments.

When a biological extract is an extract of an organism, such as an E.coli, the analysis becomes a targeted analysis for all of the compoundsin the biochemically-complex internal standard. These techniques arebased on the fact, demonstrated by many of the above authors, that boththe standard and the analyte are always suppressed to the same extent ifthey are coeluting.

Under these circumstances, the ratio of the analyte to the standardallows the calculation of the concentration of the analyte if theconcentration of the standard is known. This calculation is easilyaccomplished and the endpoint of all such studies.

However, it needs to be noted that the use of deuterium in the standardalmost always alters the chromatographic behavior of a compound, riskingthat the analyte and the standard compound will not co-elute. For thesereasons, the use of heavy stable carbon isotopes that do not changechromatographic behavior of the compound, such as ¹³C, ¹⁵N, ¹⁸O, etc.must be used.

The difficulties of techniques such as MIRACLE, where the isotopicstandards are synthesized or biosynthesized using >99% ¹³C, is that theresulting isotopic standards are difficult to distinguish from otherpeaks resulting in a large number of false data points. The IROAprotocols {de Jong²⁰, Stupp²¹, Qui²², Clendinen²³} are one solution inthat the standards are based on specific isotopic probabilities for eachcarbon, generally 5% U-¹³C and/or 95% U-¹³C. These percentages createisotopomeric patterns in the mass spectrum of each compound that areunique for each formula and, most importantly, are both easilyidentified within mass spectral scans, and will be rarely mimicked byrandom noise. Aside from the complexity of their isotopomeric clustersthey perform exactly like any isotopic standard and share almost all thephysical chemical properties of their natural abundance counterparts,except mass.

Unlike ion suppression losses, ion transmission losses have alonger-term stability but change when the electronic or physicalcharacteristics of the ion source are changed. These changes arefoundational.

Thus, unlike ion suppression, which is continuously changing, iontransmission variances can make it difficult to directly compare theresults for one sample or experiment with the results seen even in areanalysis of the same samples that are analyzed after the source hasbeen altered, but do not, in general, effect a single analytical body ofresults. Although sources seem like fairly simple devices, altering theangle of the effluent spray during the initial ion generation, changingthe voltages for any of its surfaces, or lenses, or adjusting orcleaning the capillary or other internal surfaces, among so many otherthings, alters the numbers of ions that are transmitted in the massspectrometer, rendering comparison of samples run at different timesdifficult to useless. Whereas efforts are frequently made to reduce theoverall level of transmission losses, little effort has been made tocorrect for it.

Sample-to-sample normalization, like suppression, is a wellcharacterized area of study and there are many methods for thenormalization offered {Li²⁴}. Normalization is critical whenever samplesare of different sizes, dilutions, or are be biologically dissimilar.Thus, most common sample types, e.g. urine (variance from dilution),plasma (variance by dilution), biopsies (variance from mixed cellpopulations), experimentally grown cells (variance from number of cellsin each growth), etc., can benefit from normalization. Despite thiscriticality, normalization is not commonly encountered in published databecause there is no generally accepted way to achieve it, and mostmethods yield different results because they are based on differentprinciples. Because none of the normalization methods publishedconsiders the effects of suppression, although they do a better job thanusing un-normalized data, the uncorrected variances of the suppresseddata mean that they cannot achieve an accurate normalization.

The invention disclosed hereinafter extends methods described in thefollowing U.S. Pat. No. 7,820,963, the basic IROA patent, issued Oct.26, 2010, referred to hereinafter as IROA963; U.S. Pat. No. 7,820,964,issued Oct. 26, 2010, and referred to hereinafter as IROA964; U.S. Pat.No. 8,168,945, issued May 1, 2012, referred to hereinafter as IROA945;U.S. Pat. No. 8,536,520, issued Sep. 17, 2013, referred to hereinafteras IROA520; U.S. Pat. No. 8,969,251 that issued Mar. 3, 2015, isreferred to hereinafter as IROA251, and U.S. Patent ApplicationPublication U.S. 2018/0315587 A1, published on Nov. 1, 2018, andreferred to herein as IROA587. These patents, application and the artcited therein are incorporated herein by reference.

BRIEF SUMMARY OF THE INVENTION

A method of correcting for in-source or transmission losses of ionsduring mass spectral (MS) analytical analysis and using for thecorrected ion data to normalize for sample-to-sample differences iscontemplated. In accordance with this contemplated method, an analyticalsample is mass spectrally-analyzed to provide raw data of peak sets ofparent and one or more daughter peaks indicative of each of thecompounds present. The analytical sample is comprised of two portions ofbiologically-produced and/or semisynthetically-produced compounds havingmolecular weights of about 60 Da to about Da 100,000.

A first portion of that analytical sample is comprised of elements whoseisotopes are present in their naturally abundant amounts (firstisotopes). The second portion provides isotopically signed compoundsthat may be present in the first sample (second isotopes). The isotopicsignature is provided by the presence of stable second isotopes of oneor more of the naturally abundant first isotopes of the elements of thefirst portion other than hydrogen and deuterium. The contemplatednaturally abundant isotopes are typically of lower molecular weightrelative to the isotope of the same element in the second portion. As aconsequence, the compounds that are present in both the first and thesecond portions are isotopomers.

For ease of understanding, 12C and 13C are usually used throughout thisdocument as exemplary of first and second isotopes. Those isotopes arealso preferred for use herein.

In that analytical sample, a first portion is the natural isotopicabundance C12 experimental sample and a second portion is a chemicallycomplex Internal Standard sample containing about 50 to about 10,000isotopically signed C13-containing compounds that may be present in theexperimental sample. The compounds present in both the natural abundancesample and the Internal Standard sample are referred to as pairedcompounds and their MS peaks are referred to as paired peak sets.

The summed height of the peaks of a given compound's peak set canprovide a relative measure of the amount of that compound present in itsportion of the analytical sample. The sum of the areas under acompound's peak set also provides a relative measure of the amount ofthat compound present in its portion. Thus, summing the heights or areasof a peak set of paired compounds present in each portion anddetermining the ratio of summed height to summed height, or summed areato summed area for those paired compound peaks provides a ratio of therelative amounts of the two isotopes, e.g., 12C/13C, present in thecompounds of both portions.

Each of the paired peak sets is separately corrected for ion losses andthe resulting corrected value is used for determination of aNormalization Factor. For this aspect, in-source ion losses arecorrected for each compound by correcting its Internal Standard to avalue that is an experimentally determined constant value and is alwaysthe same to provide a loss-corrected Internal Standard value. TheC12/C13 ratio for each compound assayed in each analytical sample isdetermined as the total area or peak set heights of all naturalabundance C12 peaks for the compounds as seen in the raw data divided bythe total area or peak set heights, respectively, of all InternalStandard C13 peak sets for the compounds as seen in the raw data. Theloss-corrected natural abundance value for the natural abundancecompounds is determined by multiplying the loss-corrected InternalStandard value by the C12/C13 ratio for each of those compounds.

A Normalization Factor is determined for all corrected paired peakcompounds using a normalization algorithm that utilizes summingtechnology with all corrected values so obtained for all paired peaksets for both the natural abundance and the Internal Standard portionsof the analytical sample. The sum of the Internal Standard portion isthe sum of the loss-corrected Internal Standard values for all compoundspresent in both analyte portions, and the sum of the natural abundanceportion is the sum of the loss-corrected natural abundance values forall compounds present in both analyte portions.

In one embodiment, a Normalization Factor for each analytical sample iscalculated by dividing the sum of the natural abundance portion by thesum of the Internal Standard portion. The data for each assayed naturalabundance compound of the analytical sample is normalized by multiplyingeach individual loss-corrected natural abundance value by the inverse ofthe Normalization Factor to provide a normalized natural abundancevalue.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings forming a portion of this disclosure,

FIG. 1 is a graph showing a theoretical 12C signal for any compound inplotting the MS raw data signal obtained as a function of injectedaliquot size;

FIG. 2 is a graph showing a theoretical 13C signal for any compound inan Internal Standard plotting the MS raw data signal obtained as afunction of injected aliquot size;

FIG. 3 through FIG. 8 were prepared using data obtained from the“Example” discussed hereinafter that utilized human plasma samples asbeing illustrative. FIG. 3 is itself a graph showing plots of raw MSTUSC12 values (diamonds) and corrected MSTUS C12 values (squares) obtainedversus injected aliquot size, clearly showing that the raw values do notdouble with a doubling of the aliquot volume;

FIG. 4 shows a base ratio of C12 to C13 across all samples with acorrelation of 0.9967;

FIG. 5 is a graph showing frequency versus percent ion suppression forall of the compounds assayed that illustrates that all compounds showedsome level of ion suppression;

FIG. 6 is a graph showing MS signal values versus aliquot size inmicroliters for a compound of the formula C₉H₁₆N₂O₅, wherein raw valuesare shown as circles and corrected values are shown as diamonds, andshowing that compounds with very high levels of ion suppression are notcorrelated to their concentrations, noting that suppression of 91.8% wasnoted at an aliquot size of 400 μL, and noting that peak height or areais negatively correlated to injected concentration at this level;

FIG. 7 is a graph showing MS signal values versus aliquot size forcorrected C12 values (squares) and normalized values (triangles);

FIG. 8 is a graph that plots MS signal versus aliquot size for a stearicacid sample in which raw data values are shown as diamonds, normalizedvalues are shown as squares and expected values are shown as triangles,that illustrates that normalization of compounds without InternalStandards are correctly normalized but retain suppression because thosevalues could not be corrected for without an Internal Standard; and

FIG. 9 is a graph showing that the total area under the curve for allcompounds (MSTUS) is severely affected by suppression (circles), whereasthe correlation for corrected MSTUS-IS values (diamonds) had zerostandard deviation and was thus perfect to calculate.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The present invention contemplates a method of correcting for in-sourceor transmission losses of ions during mass spectral (MS) analyticalanalysis and using for the corrected ion data to normalize forsample-to-sample differences. In accordance with this contemplatedmethod, an analytical sample is mass spectrally-analyzed to provide rawdata of peak sets of parent (base) and one or more daughter peaks thatare indicative of each of the compounds present.

It is to be understood that in most MS analyses, a single compoundprovides a base (parent; tallest) peak and one or more daughter peakswhose heights are less than that of the parent and dependent, interalia, on a number of well-known factors, particularly the amount ofnaturally non-most abundant isotopes present in an assayed compound. Asa consequence, each analyzed compound typically provides a plurality ofdata values that appear as MS peaks, and are referred to herein as “peaksets” for each compound present and assayed.

The analytical sample is comprised of two portions referred to herein asthe first and second portions that are biologically-produced and/orsemisynthetically-produced (discussed hereinafter) compounds havingmolecular weights of about 60-75 Da to about Da 100,000. The molecularweights of the compounds examined are typically of a narrower range,with the studied range being a function of the machine used and thesample preparation techniques utilized.

One preferred weight range is about 60 Da to about 2000 Da. Anotherpreferred range looks to compounds of 1000 Da or less to about 60 Da.[Molecular weights expressed as Daltons (Da) and atomic mass units (AMU)are used interchangeably herein.]

A first portion of an analytical sample is comprised of elements whoseisotopes are present in their naturally most abundant amounts (firstisotopes). A second portion provides isotopically signed compounds thatmay be present in the first sample (second isotopes).

An isotopic signature (sign) is provided by the presence of a stablesecond isotope of one or more of the naturally most abundant firstisotopes of the elements of the first portion. The contemplatednaturally most abundant isotopes of the first portion are usually oflower molecular weight relative to the isotope of the same element inthe second portion. The compounds that are present in both the first andthe second portions are called isotopomers.

A stable naturally non-most abundant isotope is stable to radioactivedecay. Illustrative examples of first and second isotopes of the sameatom are one or more elements selected from the group consisting ofisotopes of carbon (C12 and C13), nitrogen (N14 and N15), oxygen (O16,O17, or O18), sulfur (S32, S33, S34, or S36), chlorine (C135 and C137),magnesium (Mg24, Mg25 and Mg26), silicon (Si27, Si28 and Si29), calcium(Ca40, Ca42, Ca43, and Ca44), and bromine (Br79 and Br81). First andsecond isotopes are other than hydrogen and deuterium.

For ease of understanding, 12C and 13C are usually used throughout thisdocument as exemplary of first and second isotopes. Those isotopes arealso preferred for use herein.

In that analytical sample, a first portion is the natural isotopicabundance C12 experimental sample and a second portion is a chemicallycomplex Internal Standard sample containing about 50 to about 10,000isotopically signed C13-containing compounds that may be present in theexperimental sample. The number of such isotopically signedC13-containing compounds is narrowed to about 50 to about 2000 in somepreferred embodiments. Such narrowing can be accomplished by adjustmentof chromatographic techniques as is well known.

An experimental sample portion of an analytical sample is typically ofbiological origin such as serum, plasma, urine, lymph or other bodyfluid or product such as feces, a cell culture lysate, minced plantanimal or fungal tissue. An experimental sample portion can alsooriginate from a laboratory chemical reaction in which a reactioncomposition containing one or more reactants, products and side productsare present.

The compounds present in both the natural abundance sample and theInternal Standard sample are referred to as paired compounds(isotopomers) and provide paired peak sets on MS analysis. The summedheight of the peaks of a given compound's peak set can provide arelative measure of the amount of that compound present in its portionof the analytical sample. The sum of the areas under the curve of acompound's peak set also provides a different relative measure of theamount of that compound present in its portion.

Thus, summing the heights or areas of a peak set of paired compoundspresent in each portion and determining the ratio of summed height tosummed height, or summed area to summed area for those paired compoundpeaks provides a ratio of the relative amounts of the two isotopes,e.g., 12C/13C, present in the compounds of both portions.

Each of the paired peak sets is separately corrected for ion losses andused for determination of a Normalization Factor. For this aspect,in-source ion losses are corrected for each compound by correcting itsInternal Standard to a value that is an experimentally determinedconstant value and is always the same to provide a loss-correctedInternal Standard value. The C12/C13 ratio for each compound of acompound pair assayed in each analytical sample is determined as thetotal area or peak set height of all natural abundance C12 peaks for thecompounds as seen in the raw data divided by the total area or peak setheight, respectively, of all Internal Standard C13 peak sets for thecompounds as seen in the raw data. The loss-corrected natural abundancevalue for the natural abundance compounds is determined by multiplyingthe loss-corrected Internal Standard value by the C12/C13 ratio for eachof those compounds.

A Normalization Factor is determined for all corrected paired peakcompounds using a normalization algorithm that utilizes summingtechnology with all corrected values so obtained for all paired peaksets for both the naturally most abundant and Internal Standard portionsof the analytical sample. The sum of the Internal Standard portion isthe sum of the loss-corrected Internal Standard values for all compoundspresent in both analyte portions, and the sum of the natural abundanceportion is the sum of the loss-corrected natural abundance values forall compounds present in both analyte portions.

A Normalization Factor for each analytical sample is calculated bydividing the sum of the natural abundance portion by the sum of theInternal Standard portion. The data for each assayed natural abundancecompound of the analytical sample is normalized by multiplying eachindividual loss-corrected natural abundance value by the inverse of theNormalization Factor to provide a normalized natural abundance value.

In one preferred embodiment, the isotopic signatures of the pairedcompounds conform to an IROA pattern as is described in U.S. PatentApplication Publication U.S. 2018/0315587 A1 and the related patentdocuments noted previously. In another preferred embodiment, aloss-corrected Internal Standard value for each compound is anexperimentally determined value obtained from data of another analysis;i.e., an analysis other than that recited in the claims. In anotherembodiment, a loss-corrected value for each compound in the InternalStandard is retrieved from a database of assigned values. In yet anotherembodiment, a loss-corrected Internal Standard value for each compoundis an experimentally determined from the data in the current or recited(claimed) analysis.

In another preferred embodiment, isotopic signatures are providedsemisynthetically by separately reacting compounds of the first portionand second portion of the analytical sample with one or the other of anisotopomeric reagent pair containing the same reactive group that reactswith and bonds to a functional group of one or more paired compoundspresent in the analytical sample portions. In this embodiment, separatereaction of the compounds of the first portion and second portion of theanalytical sample with one or the other of an isotopomeric reagent pairis carried out prior to admixture of said first portion and said secondportion to form the analytical sample.

Thus, illustratively using cell cultures as the source of the twoportions, one can lyse the cells and separately react the resultantlysates with one or the other of the isotopomeric reagent pair providinga defined signature such as an IROA signature or similar pattern,separate the insoluble cell debris from the remainder as bycentrifugation, and mixing the resulting two supernatants to form theanalytical sample preparation. Alternatively, the desired isotopomericlabeling reactions can be carried out on each of the supernatantsfollowed by admixture to form an analytical sample composition.

The phrase “analytical sample” is therefore used herein as a genericphrase intended to encompass both an “analytical sample preparation” andan “analytical sample composition”, as use of either provides enhancedresults over the prior art. Use of an “analytical sample composition” ispreferred if only because more isotopomeric reagent is needed toadequately react with cellular contents including debris, and wouldtherefore be wasteful.

Once formed, an analytical sample is typically physically separated bygas chromatography (GC) or more usually liquid chromatography (LC) orhigh pressure liquid chromatography (HPLC) and the eluate is thenprovided to a mass spectrometer for mass spectractral (MS) analysis. Theseparation technique is thus often referred to in modern literature asLC-MS.

Analytical samples are made by mixing an experimental sample (to beanalyzed), such as a biological extract, with a constant amount of achemically complex isotopically distinguishable Internal Standard. As aminimal definition, the Internal Standard contains a reproducible set ofcompounds at reproducible concentrations and can be used repeatedly,ideally for at least five to ten years; however, shorter term internalstandards can be made to work using this method wherein the results areonly be comparable for shorter periods of time.

In one preferred embodiment, the chemical composition of the InternalStandard matches small molecular weight compounds (e.g., less than about2000 Da and more usually less than about 1000 Da) of the completechemical composition of the experimental sample. However, the naturalchemical variance of the experimental samples excludes perfection. Thelower weight limit for a biologically-produced metabolite is about 60-75AMU as in acetic acid and glycine. Therefore, the Internal Standardpreferably has at least about 50 compounds found in all experimentalsamples. The Normalization is better as the number of commonly foundcompounds increases.

Because of the chemical complexity of the Internal Standard, allanalytical samples can be viewed as consisting internally of twocomplete samples; the experimental sample and the Internal Standardsample. After the analytical samples are analyzed, software such asClusterFinder™, mzMine, mass-hunter, or similar such software is used tofind and quantitate all of the peaks found in each sample.

Each of the peaks from the Internal Standard should be identified asderived from the Internal Standard, and each of the peaks from theexperimental sample should be identified as derived from theExperimental sample. For each analytical sample all cases in which thesame compound is found in both the Experimental and Internal Standardsshould be identified and can be called the “commonly found list”.

For all compounds in the “commonly found list” there will be a massspectral response for both the compound originating from theExperimental sample and its isotopomer originating from the InternalStandard. This response can be in the form of area under the curve (orsummed peak height), the height of the monoisotopic, or other standardmeasures may also be used. The response seen is referred to as the “rawC12 response” and the “raw IS response”, respectively. It is well-known,and demonstrated in the Example hereinafter, that such raw responses arenot correct universal reflections of the concentrations of theirunderlying compounds due to the presence of significant variances in thegeneration and transmission of the ions in the source, and other partsof the mass spectrometer.

In addition to these raw values, a raw “C12/C13 ratio” can be calculatedby dividing the “raw C12 response” by the “raw IS response”. Thus, fromthe analytical data for all compounds found we can derive three values,“the “raw C12 response”, the “raw IS response”, and the “C12/C13 ratio”.

The first two are known to be imperfect reflections of their truevalues, but the third is understood by skilled practitioners to be anaccurate reflection of the ratio of the original true values because itis accepted that the losses suffered in the analytical processes will beapplied equally by both sides.

For the Internal Standard, if the accurate original value; i.e., aresponse that suffers no, or minimal, loss is known then the “raw ISresponse” can be replaced with a “corrected IS response” and the“corrected C12 response” can be calculated by multiplying the “correctedIS response” by the “C12/C13 ratio”.

The accurate original value can be determined either experimentally ordetermined once for each Internal Standard, recorded and then this valueis subsequently retrievable by software as needed. Because the error inthe raw response is its variability, to one versed in the art theprecision of the “accurate original value” is less important than theuse of a constant and reproducible value multiplied by the “C12/C13ratio”.

The losses in the raw data vary by both time and compound in a complexway. Some losses are due to the nature of each specific chemicalstructure and vary within each sample as the environment in which thecompound is caused to ionize changes.

It is similarly well known that other losses are imposed broadly on allcompounds as a function of the physical parameters of the Ion Sourcechange. These latter losses have much longer timelines, but when theychange they make samples from before and after directly incomparable.Although there are approaches to compensating for such long-term losses,they are required to make assumptions that the underlying samples areactually comparable, which may or may not be true.

The technique described here correct for both of these types of lossesand does so quite accurately using first principles that are generallyaccepted by all in the field but have never been implemented. The use ofa standard value for the accurate original value is particularly usefulas it specifically overcomes the longer-term changes.

Having corrected for ion losses there is still a problem that has notbeen solved, namely the fact that the samples may have different sizes,as discussed above this can make even samples with corrected resultsincomparable to other samples. This problem is commonly called anormalization problem. As discussed earlier, there are many approachesto normalization.

A summing-type normalization algorithm is useful for overcoming thesample size difference problem. Several such algorithms are discussed in{Li²⁴} and particularly in Table 1 of that publication. Illustrative ofthose summing-type algorithms are those referred to as autoscaling,Level scaling, Mean scaling, median scaling, MSTUS, Pareto scaling,power scaling, Range scaling, Total sum, Vast scaling. MSTUS is utilizedillustratively herein.

An R script (version 3.4.2) was used to model the calculations anddevelop the algorithms for suppression correction and MSTUSnormalization. Briefly, all the peaks used in the algorithms had minimumcriteria: 1) they had to be present in all samples, 2) they had to beabove a minimum peak area (or height), and 3) and the ratio between theC13-IS and the C12 monoisotopic peaks had to be greater than 0.001. Asto criterion 1), the peaks used can be present in both portions so thatthe number calculated varies sample by sample, or in present all samplesso that the same set is used, so that preferably, the peaks are presentin both and/or all samples.

The original dataset had 389 IROA peaks found in all 16 samples, 232 ofthese peaks met the acceptance criteria and were used for MSTUSnormalization. Note that the MSTUS normalization has always used asubset of the entire dataset for normalization. A subset and even asubset of the found IROA peaks is used in the algorithm, but becausethey are all IROA peaks all assured to be of biological origin, and with232 compounds being considered there are plenty to determine the MSTUSratios needed.

For all the peaks the suppression-corrected C12 values were used as theyare a better reflection of the true concentration found in the sample.These suppression-corrected values were determined by multiplying theleast suppressed C13-IS value by the ratio of the C12 and IROA AUCs.(These ranged from 0.001 to 98.5.) The C13-IS values were fixed at theleast suppressed value seen for that particular IS compound.

For normalization, the MSTUS sum for the C12 side was divided by theMSTUS sum for the C13 side to obtain a correction factor in that whenevery compound was multiplied by this factor, the sum for every compoundin the original sample (MSTUS C12) would be equal to the sum of all thesuppression-corrected IS values. Because these samples are chemicallyidentical, the proof of the normalization is that the values oncenormalized are the same. For a “normal” sample in which the chemicalbalance varies, the normalization makes the two sides equal but does notdisturb the concentration relationships between the compounds.

Results and Discussion

Because the IROA Internal Standard (IROA-IS) is always present at thesame concentration, the plot of the total area (or height) of all ISpeaks (MSTUS-IS) should match the theoretical plot shown in FIG. 2.However, the MSTUS-IS raw values show significant cumulative effect fromthe overall suppression of its constituent peaks as concentrationincreases as is seen in FIG. 9 as compared to the corrected values.

Similarly, according to the experimental design, the raw naturalabundance MSTUS-C12 signal should increase predictably, as demonstratedin FIG. 1. However, in this case, as shown in FIG. 3, the actual rawdata deviate because of the overall suppression affecting most of thecompounds in the sample, resulting in a value that is almost 60% lowerthan it should be.

The above discusses the MSTUS values or the sums across all compounds inthe MSTUS set. When individual compounds are examined, for instanceL-tyrosine, suppression is evident in all samples except the lowestconcentration. In the highest concentration samples, a suppression of29.1% appears to be evident using the equation:

(SC-C12−rawC12)/SC-C12

where SC-C12 is the average value of the Suppression-Corrected C12, andrawC12 is the average value of the uncorrected peaks in the samesamples. It is clear from this dataset that virtually every compoundexhibits some suppression, and so do their internal standards.

Therefore, it is no surprise that the IROA tyrosine Internal Standard isnot only suppressed but shows exactly the same level of suppression asits natural abundance counterpart (a number independently determined).Despite the suppression of both the analyte and the Internal Standard,the ratio of the IROA IS area (or height) to the analyte area (orheight) is exactly consistent with experimental design. This is notsurprising because they are subject to the same environment duringionization process, and the carbon isotopes the IROA employs should nothave any significant effect on ionization properties.

It has recently been shown that the IROA isotopomer collections behaveidentically in Ion Mobility, and predictably similar in fragmentation.Except for mass, the IROA isotopomeric peaks for any given peak willbehave uniformly.

As discussed hereinafter, the 232 compounds examined and used incalculations had to have a base peak larger than 250,000, and a ratio atthe lowest concentration of at least 0.001. The range of suppression forall of the compounds in this collection is about 6% to about 92% (FIG.5). The majority of compounds appear to be suppressed at about 20 toabout 60 percent. At very high levels of suppression, some compoundswere so severely suppressed they were negatively correlated to theiractual concentration as can be seen for the C₉H₁₆N₂O₅ compound of FIG.6. It is noted that the base peak value of 250,000 is machine-specific,and varies from machine to machine.

Because the analyte to IROA-IS ratio for every compound correctlyreflects the original concentration of the analyte relative to theIROA-IS, a suppression corrected value can be determined by setting theIS equal to its least suppressed value (accepted to be the highest valueseen experimentally) and multiplying this value by the ratio todetermine what a reasonable suppression corrected value may be.

Although any number can be used to act as the constant in place of the“least suppressed value”, the use of the actual least suppressed valuehas the benefit of retaining the approximately correct amplitude for thepeaks in question. Therefore, it is relatively easy to computesuppression corrected values for all compounds found. The formula forC12 suppression correction is:

X*C12/IROA-IS ratio

where X can be any value, but the least suppressed observed value is ofthe normal amplitude. Similarly, in the absence of suppression theIROA-IS is a constant and therefore it is always assigned the samevalue.

The MSTUS algorithm is typically used to normalize NMR and LC/MS-basedmetabolomics data, especially highly variable samples such as urine.However, it is clear that MSTUS is not a perfect solution as it does notaccount for noise in the dataset. This noise is the result of theinclusion of artifactual data, causing extreme suppression which in turnstrains the underlying rational for MSTUS itself.

In IROA noise is automatically removed as it does not exhibit an IROAprofile. Thus, using a suppression-corrected value for all IROAcompounds, a MSTUS algorithm can now be applied to this correcteddataset to achieve a better result. Furthermore, because an IROAinternal standard has been added, there are two physical samples present(the natural abundance sample, which constitutes the analytes, and thereference IROA-IS sample), and a true normalization relative to theinternal standard can be performed, with the removal of noise that wasnot previously possible.

The unique carbon envelope of associated peaks for each analyte in theIROA-IS (e.g., 95% C13) ensures removal of artefactual data. Specific(ClusterFinder™) algorithms are used to search for these envelopes andthen identify their associated peaks in the natural abundance peaksamples. Any feature without a match is eliminated, removing noise andartifactual data. The calculation for the MSTUS normalization correctionfactors is:

sumSCC12/sumSCIS

where sumSCC12 is the total suppression-corrected area (or height) ofall considered C12 compound peaks, and sumSCIS is the totalsuppression-corrected area (or height) of all considered IS compounds.

The suppression-corrected values are multiplied by these factors tonormalize them all to the same base. The normalized MSTUS value is thesum of all normalized values. In a normal metabolomic study, wheresample sizes and chemical constituents are varying, the normalizationcorrects for differences in sample sizes or preparation; i.e., changesthat effect the entire preparation, and the normalized sums differbecause of the differences in chemical composition.

In the design of this experiment, and only in this experiment, since thesamples were chemically the same the normalization should normalize allsamples to be identical, and do so (not shown). The combination of theIROA and MSTUS approach provides a reproducible means to generateion-suppression-corrected data that can be effectively normalized toachieve accurate measurements. Due to there being two data sets, acombined MSTUS summing approach can be used to better accommodate thetwo data sets.

EXAMPLE

Sample Preparation

For each of three replicates (n=3), 75 μL of a common human plasmasample (containing K2-EDTA as anti-coagulant) were added to apolypropylene microcentrifuge tube followed by 1.5 mL of dry ice-cooledmethanol, and the pooled solution was centrifuged at 16,100 g at 4° C.for 10 minutes. The supernatant was transferred to a new tube from whichaliquots of 400, 200, 150, 100, 75, and 50 μL were prepared.

The methanolic aliquots were then dried using a centrifugal vacuumconcentrator and stored at −80° C. Immediately before LC-MS analysis,the dried residues were resuspended in 40 μL of TQ-IS (TruQuant™ C13 IS;IROA Technologies) solution which contained 20 μg of C13 IS.

The C13 IS solution was prepared by dissolving the contents of an TQ-ISvial containing 0.6 mg of a biologically complex mixture fully labeledat 95% C13 in 1.2 mL of H₂O, vortexed, and briefly centrifuged. Thecontents of the tube were then transferred to a polypropyleneautosampler vial.

TQ-LTRS (TruQuant™ Long-Term Reference Standard, IROA Technologies) wasprepared by dissolving the contents of an TQ-LTRS vial containing 20 ugeach of a biologically complex mixture fully labeled at both 5% and 95%C13 in 40 μL of H₂O. Three μL of TQ-LTRS and 5 μL of each preparedplasma sample were analyzed by making triplicate injections using bothpositive and negative ionization and hydrophilic interactionchromatography (HILIC) and reverse phase liquid chromatography (RPLC).

Pooled plasma was extracted using −80° C. methanol (methanol:plasma,20:1). Six replicate aliquots of pooled extract at 150, 200, 250, 300,350, 400, 450, 500, and 550 μL were delivered to vials, dried using acentrifugal vacuum concentrator, and stored at −80° C.

For analysis, samples were reconstituted with 40 μL of the TQ-IS (orIROA-IS) in distilled water. The TQ-LTRS was resolvated by addition of40 μL distilled water. Samples were randomized and analyzed according totheir respective chromatographic systems LC-MS.

The chromatographic system consisted of a Phenomenex Kinetex™ HILICcolumn (1.7 μm, 100 Å, 100×2.1 mm) as well as a Phenomenex Kinetex™ C18column (2.6 μm, 100 Å, 150×2.1 mm) C18 column, and the columncompartment was kept at 40° C. Solvent A consisted of water containing10 mM positive ammonium acetate and 0.1% formic acid and solvent B wasmethanol containing 10 mM ammonium acetate and 0.1% formic acid.

A flow rate of 200 μL/minute was used throughout the duration of thechromatographic run. From 0 to 5 minutes the solvent composition washeld constant at 5% solvent B. The solvent composition then ramped from5 to 95% solvent B from 5 to 30 minutes. A solvent composition of 95%solvent B was next maintained from 30 to 40 minutes. Finally, thesolvent composition was returned to 5% solvent B and held constant from40 to 45 minutes.

Mass spectrometry was performed on a Thermo Scientific™ Orbitrap Fusion™Lumos™ Tribrid™ operated in FTMS full-scan mode with a scan range of70-650 m/z and a resolution of 240,000. For heated electrospray positiveionization, a spray voltage of 3500 was used and the vaporizer andcapillary temperatures were set at 250 and 375° C., respectively. Thesheath, auxiliary and sweep gas pressures were 35, 10, and 0 (arbitraryunits), respectively.

Data Analysis

Data were analyzed using ClusterFinder™ software (version 3.1—IROATechnologies).

The TQ-IS (or IROA-IS) is a biochemically complex Internal Standard.TQ-IS and TQ-LTRS are part of the TruQuant™ workflow from IROATechnologies. The use of these reagents here is illustrative, the methoddescribed here works with other isotopic labeling systems that contain asufficient number of compounds to ensure the MSTUS normalization isaccurate. The TQ-IS is used with a matching TQ-LTRS to find, list andqualify all the compounds in the TQ-IS. The use of TQ-LTRS is notrequired. In this study we found and analyzed the suppressive responsefor 102 compounds that were present in both the internal standard andthe samples.

The experimental design employed in this experiment is extremely simple;namely, varying aliquot sizes, in triplicate, of a single homogeneoussolution, here an extract of human plasma, are delivered and dried undera gentle nitrogen stream. Because the source and chemistry of everysample emanates from a single homogeneous solution and vary only byvolume, even though its absolute concentration may not be known, therelative quantity of every compound in every sample should increase inproportion to the volume of the original aliquot and when plotted shouldcorrespond to the FIG. 1.

Once dried, every sample is resolvated with a constant volume of aninternal standard, in this case 40 μL, and therefore the quantity ofevery compound in the internal standard should be constant andcorrespond to the graph shown in FIG. 2. The samples were injected inrandom order and the resulting data were examined.

FIG. 3 (diamonds) shows the average response seen for all analyticalcompounds, but as can be seen, it does not correspond to its expectedcurve (FIG. 1). In this case the observed values are lower than theexpected values and show a stronger deviation as the concentrationincreases, making it clear that the dominant, if not sole, effect seenhere is suppression.

On the other hand, the theoretical ratio of the AUC for each analyte toits corresponding internal compound for all compounds; i.e., the“C12/C13 ratio”, is shown in FIG. 4, and this does correspond to theexpected curve (FIG. 1). Therefore, it is clear, as previous researchhas shown, that the overall analyte to internal standard ratio isunaffected by ion suppression, as long as the isotopes in the internalstandard are C13; i.e., the ionization rates of internal standard andits corresponding analyte are generally suppressed to the same extent.

Furthermore, the least suppression will occur in the samples with thesmallest aliquots of sample. Therefore, the average value for internalstandard for the triplicate samples with the smallest aliquot wasconsidered the least suppressed value for our first approximations.

Given the above-discussed observations we considered the following knownand true facts: 1) it is known that the concentration for every internalstandard compound in every sample is present at a constant value, 2) ithas been shown that the analyte-to-internal standard ratio for allcompounds appear to correctly reflect the original concentrationregardless of suppression because 3) the analyte and its correspondinginternal standard are equally suppressed, therefore:

1) One can correct the observed internal standard value by supplying theoriginal “unsuppressed” value for the internal standard as the correctedvalue for the internal standard, and

2) multiplying this same value by the analyte-to-standard ratio todetermine the correct value that the analyte would have had had it notbeen suppressed.

These values were quite easy to calculate for every compound internalstandard and analyte pair, and raw and corrected values are seen in FIG.3 (diamonds=raw data, squares=corrected data). The corrected datacorresponds well with the theoretical graphs (FIG. 1).

In the calculations for this study we have used the values for theinternal standard as seen in the samples with the lowest analyteconcentration as an estimate of the “unsuppressed value”. It isundoubtedly true that even this value is subject to some suppression.However, if one considers the math, it is easily recognized that thevalue itself is of less importance than that the value be a constantvalue of appropriate amplitude as such a value can be used to overcomeboth short and long term in-source losses.

The value we have used in this analysis has the correct approximateamplitude relative to all other compounds and we think this is of someminor benefit. Indeed, it may very well be that the establishment of asingle value that is always used as a “standard value” for each compoundin the Internal Standard provides a general mechanism for the creationof “standard corrected spectra” that remove the need to “normalizespectra against one-another when experiments run across multiple days,months, or even some changes to instrumentation; i.e., to overcome notjust sample to sample error.

Instrument drift issues are different in that they are imposed as agross source of variance on a majority of all mass spectral signals foran extended period of time but are also subject to random changes withtime. It may be understood that this to may be corrected for. If youhave a ratio that is always based on a standard amount of internalstandard, and a fixed SOP the prior discussion makes it clear that youcan calculate the correct value of the analyte using the methoddiscussed above.

An analysis of the corrected to raw values indicates the range ofsuppression seen in this experiment was about 6% to about 91.8% (seeFIG. 5). It is surprising that there were no compounds that did notsuffer from any ion suppression. However, the overall shape of thedistribution and the fact that the median is approximately 40% supportsthis observation. It is likely that there are compounds that are morehighly suppressed than 91% however with so few ions surviving it is notsurprising these compounds may be difficult to see. Compounds that aresuppressed greater than 80% are generally negatively correlated to theirinjected concentration and compounds from 60% to 80% are essentiallyflat irrespective of the injected concentration (see FIG. 6). Thesefacts strongly indicate why the correction of the raw data is soimportant.

The above corrections only correct for ion losses, they do not correctfor variances in sample sizes or concentration, technically referred toas “normalization”. Given the above results and discussion, it should beclear that the raw data is a sufficiently inaccurate reflection of theactual concentrations of most compounds that any normalization based onraw data contains a significant amount of error. The normalizationstrategy we employ here has two novel facets, firstly it uses datacorrected for ion-losses, as noted above, and secondly, since there is acomplete standard sample embodied in every analytical sample theexperimental sample is normalized to it conjoined internal standard.

The first strategy facet reduces the overall variance of the entiredataset by correcting for all ion losses. The second facet normalizesthe corrected dataset to a corrected “Standard” sample, and in doing somakes the experimental sample indirectly comparable to any otherexperimental sample normalized to the same “Standard” sample. Themechanism is straight forward: in correcting for ion losses we correctedboth the experimental portion and the Internal Standard portion forevery compound; therefore the MSTUS summing preferably also sums overthe sample to provide the “sum of all corrected values in theexperimental sample” be calculated, and the “sum of all corrected valuesin the Internal Standard sample” be calculated.

Then the “normalization factor” is the “sum of all corrected values inthe experimental sample” divided by the “sum of all corrected values inthe Internal Standard sample”. Once calculated, all corrected values arenormalized by multiplying the corrected value for each compound by the“normalization factor”. Once normalized, the samples appear to of thesame size despite any physical sample-to-sample differences (see FIG.7).

Although the need for normalization is more obvious for samples such asurine, where concentrations are quite variable, it is surprisingly hardto handle very small biopsies, or other physical samples as significantvariances are introduced during preparation, as moisture content, andphysical losses routinely occur. This dual MSTUS algorithm adjusts allsamples for all such valiances. The experimental data shown in FIG. 7may represent an extreme case for normalization, but its success heremakes it clear it will work in all situations.

The normalization factor calculated from the loss corrected compounds isactually applicable to the all of the compounds found in theexperimental sample whether they have a matching internal standard ornot. For this reason, the normalization factor can be applied touncorrected peaks where there may be no opportunity to correct them andthese compounds will be correctly normalized but will still show thesuppression losses (see FIG. 8). Even though it is not possible tocorrect for ion losses, the normalized values are more accurate than theraw values.

What should be clear from this discussion is that by use of a chemicallycomplex internal standard it is possible to correct for many of themajor sources of variance in any mass spectral data set, and that oncecorrected that samples may be normalized to one another using theInternal Standard as the basis of a dual MSTUS algorithm. These combinedactions effectively correct for a majority of the errors in most massspectral analyses.

Each of the patents, patent applications and articles cited herein isincorporated by reference. The use of the article “a” or “an” isintended to include one or more.

The foregoing description and the examples are intended as illustrativeand are not to be taken as limiting. Still other variations within thespirit and scope of this invention are possible and will readily presentthemselves to those skilled in the art.

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1. A method of correcting for in-source or transmission losses of ionsduring mass spectral (MS) analytical analysis and using the correctedion data to normalize for sample-to-sample differences that comprisesthe steps of: a. mass spectrally-analyzing an analytical sample toprovide raw data of peak sets of parent and one or more daughter peaksindicative of each of the compounds present, said analytical samplebeing comprised of two portions of biologically-produced and/orsemisynthetically-produced compounds having molecular weights of about100,000 Da to about 60 Da in which a first portion is the naturalisotopic abundance of a first isotope experimental sample and a secondportion is a chemically complex Internal Standard sample containingabout 50 to about 10,000 isotopically signed second isotope-containingcompounds that may be present in the experimental sample, wherein thosecompounds present in both the natural abundance sample and the InternalStandard sample are referred to as paired peak sets; b. each of thepaired peak sets is separately corrected for ion losses and used fordetermination of a Normalization Factor, wherein i) in-source losses arecorrected for each compound by correcting its Internal Standard to avalue that is an experimentally determined constant value and is alwaysthe same to provide a loss-corrected Internal Standard value, whereinsaid experimental constant value is determined by using the value ofsamples containing the lowest concentration of analyte, ii) the firstisotope/second isotope ratio for each compound in each analytical sampleis determined as the total area or peak set heights of all naturalabundance first isotope peaks for the compounds as seen in the raw datadivided by the total area or peak set heights, respectively, of allInternal Standard second isotope peak sets for the compounds as seen inthe raw data, iii) the loss-corrected natural abundance value for thenatural abundance compounds is determined by multiplying theloss-corrected Internal Standard value by the first isotope/secondisotope ratio for each said compound, c. determining a NormalizationFactor for all corrected paired peak compounds using a normalizationalgorithm with all corrected values so obtained for all paired peak setsfor both the natural abundance and Internal Standard portions of theanalytical sample, wherein i) the sum of the Internal Standard portionis the sum of the loss-corrected Internal Standard values for allcompounds present in both analyte portions, ii) the sum of the naturalabundance portion is the sum of the loss-corrected natural abundancevalues for all compounds present in both analyte portions, iii) aNormalization Factor for each analyte sample is calculated by dividingthe sum of the natural abundance portion [ii) above] by the sum of theInternal Standard portion [i) above]; and d) normalizing across thesample of each natural abundance compound by multiplying each individualloss-corrected natural abundance value by the inverse of theNormalization Factor to provide a normalized natural abundance value. 2.The method according to claim 1, wherein a loss-corrected InternalStandard value for each compound is an experimentally determined valueobtained from data of another analysis.
 3. The method according to claim2, wherein the values for each compound in the Internal Standard areretrieved from a database of assigned values.
 4. The method according toclaim 1, wherein a loss-corrected Internal Standard value for eachcompound is an experimentally determined from the data in the currentanalysis.
 5. The method according to claim 1, wherein said first isotopeis carbon-12 (C12) and said second isotope is carbon-13 (C13).
 6. Themethod according to claim 1, wherein the isotopic signatures areprovided by first and second isotopes of the same atom other thanhydrogen and deuterium selected from the group consisting of carbon (C12and C13), nitrogen (N14 and N15), oxygen (O16, O17, or O18), sulfur(S32, S33, S34, or S36), chlorine (C135 and C137), magnesium (Mg24, Mg25and Mg26), silicon (Si27, Si28 and Si29), calcium (Ca40, Ca42, Ca43, andCa4), and bromine (Br79 and Br81).
 7. The method according to claim 1,wherein the isotopic signatures of the paired compounds conform to anIROA pattern.
 8. The method according to claim 7, wherein the isotopicsignatures are provided by a most naturally abundant isotope and one ormore of the corresponding stable isotopes selected from the groupconsisting of C13, N15, O17, O18, S33, S34, S36, C137, Mg25, Mg26, Si28,Si29, Ca42, Ca43, Ca44 and Br81.
 9. The method according to claim 1,wherein said isotopic signatures are provided semisynthetically byseparately reacting the compounds of the first portion and secondportion of said analytical sample with one or the other an isotopomericreagent pair containing the same reactive group that reacts with andbonds to a functional group of one or more paired compounds present insaid analytical sample portions.
 10. The method according to claim 9,wherein said separate reaction of the compounds of the first portion andsecond portion of said analytical sample with one or the other anisotopomeric reagent pair is carried out prior to admixture of saidfirst portion and said second portion to form said analytical sample.11. The method according to claim 1, wherein ion losses arise from iontransmission inefficiencies.
 12. The method according to claim 1,wherein the losses arise from ion suppression or ionizationinefficiencies.
 13. The method according to claim 1, wherein saidnatural isotopic abundance experimental sample containing said firstisotope is obtained from human or non-human blood.
 14. The methodaccording to claim 1, wherein said Internal Standard is biologicallyproduced.
 15. The method according to claim 1, wherein said experimentalsample is obtained from human or non-human serum, plasma, urine, feces,or other bodily secretions.
 16. The method according to claim 1, whereinsaid experimental sample is obtained from a non-biological source. 17.The method according to claim 1, wherein said experimental sample isobtained from human or non-human tissues.
 18. The method according toclaim 1, wherein said experimental sample is obtained from plants,bacteria, or fungi.
 19. The method according to claim 1, wherein saidnormalization algorithm utilizes MS total useable signal (MSTUS)technology.